Surface Protein abundance Estimation using CKmeans-based clustered thresholding ('SPECK') is an unsupervised learning-based method that performs receptor abundance estimation for single cell RNA-sequencing data based on reduced rank reconstruction (RRR) and a clustered thresholding mechanism. Seurat's normalization method is described in: Hao et al., (2021) tools:::Rd_expr_doi("10.1016/j.cell.2021.04.048"), Stuart et al., (2019) tools:::Rd_expr_doi("10.1016/j.cell.2019.05.031"), Butler et al., (2018) tools:::Rd_expr_doi("10.1038/nbt.4096") and Satija et al., (2015) tools:::Rd_expr_doi("10.1038/nbt.3192"). Method for the RRR is further detailed in: Erichson et al., (2019) tools:::Rd_expr_doi("10.18637/jss.v089.i11") and Halko et al., (2009) tools:::Rd_expr_doi("10.48550/arXiv.0909.4061"). Clustering method is outlined in: Song et al., (2020) tools:::Rd_expr_doi("10.1093/bioinformatics/btaa613") and Wang et al., (2011) tools:::Rd_expr_doi("10.32614/RJ-2011-015").
Maintainer: Azka Javaid azka.javaid.gr@dartmouth.edu
Authors:
H. Robert Frost hildreth.r.frost@dartmouth.edu